1. Field of Invention
This invention relates to systems and methods for analyzing and predicting business demand based on historical demand and changes in actual current demand.
2. Background of the Invention
In production planning for a business environment, such as a retail business offering products of short shelf life like foodstuffs, or more generally in any business requiring a series of various tasks depending on changes in demand for the business's offerings, a tendency exists toward using production plans that are calculated on an infrequent basis. This basis is often daily at best but more often is based on average daily or weekly sales. This results in excessive product and waste where demand is below production, or lost revenue where there is not enough production to meet customer demand. It is impractical, if not impossible, for a human being to calculate business demand on a more frequent basis such as hourly or every fifteen minutes, which would be more suited to determining varying business demand levels during daily operations.
In addition to the impracticality of computing business demand manually on a more frequent basis is the complexity introduced by different demand patterns for each day of the week, seasons of the year, or other recurring events. Customer foot traffic and product preferences are unique to each day of the week. These traffic patterns and preferences are further complicated by seasonality trends week by week throughout the year. In addition, promotional programs, local events, holidays, and the like, all alter the demand levels faced by a business. Accommodating this level of complexity requires storing and using the past business demand according to a model that accounts for the seasonality, day of the week, and time intervals during the business day, for each of a plurality of products or business items to determine future business demand for a specific location.
Another difficulty encountered once the past business demand has been stored is the ability to deal with incomplete data from current time periods and to compare trends in just-completed time intervals against projected demand in the equal time intervals in order to adjust the production or business item in near-future time intervals accurately and with confidence. One method for making such comparisons and projections on other near-future intervals is to take a simple positive or negative percentage of the trend of just-completed periods against projected periods and apply it to the remaining projected near future periods for the day. This method is unreliable given the many anomalies that can occur, for example, when a bus load of people arrives or an unusually large order is placed. What is needed is method of adjusting the projected demand levels in future intervals in proportion to both historical demand trends and current actual demand.